基于高光谱成像技术的海淡水鱼类识别模型研究
摘要:随着高光谱图像技术的逐渐成熟,其在肉类无损检测与识别中的应用已成为当前的研究热点之一。本文针对海淡 水鱼类的研究,通过对采集到的光谱曲线数据进行预处理和特征提取,结合BP网络结构和LVQ网络结构,初步建立了 海淡水鱼类高光谱图像数据的预测模型,最终实现了海淡水鱼类品质的定性分析与识别。
关键词:海淡水鱼类;高光谱图像技术;BP网络;LVQ网络 DOI 10.1109/IHMSC.2013.94
期刊:2013 Fifth International Conference on Intelligent Human-Machine Systems and Cybernetics
设备:GaiaField
Research on Marine and Freshwater Fish Identification Model Based on Hyper- Spectral Imaging Technology
Abstract:with the gradually mature of hyper spectral image technology, the application of the meat nondestructive detection and recognition has become one of the current research focuses. This paper for the study of marine and freshwater fish by the pre- processing and feature extraction of the collected spectral curve data, combined with BP network structure and LVQ network structure, a predictive model of hyper spectral image data of marine and freshwater fish has been initially established and finall: realized the qualitative analysis and identification of marine and freshwater fish quality.
Keywords:Marine and Freshwater Fish; Hyper-spectral image technology; BP network; LVQ network



































